Why Workday Started A Fund To Invest In Machine-Learning Startups

With annual sales of about $1 billion this year and a market cap of $15 billion, Workday has emerged as one of the leaders of the new old guard in cloud computing. But as it branches out into new areas of focus further afield from its human-resources software background, Workday's planning to commit serious dollars to stay close to the trends of startups more on the cutting edge.

That's the impetus behind Workday launching a new fund, Workday Ventures, with the mandate to invest in machine learning and data science-focused startups. Workday's already invested in four such companies across early stages and plans to identify a lot more in the next several years.

"Workday is a ten-year-old company, but we still try to be cool," says Dan Beck, senior vice president of product marketing and technology at the company. "For eight and a half of those years, we weren't doing cool things with data yet."

That started to change back in Feb. 2014, when Workday acquired analytics startup Identified. That brought into the fold Identified cofounder Adeyemi Ajao, a Spanish national and now vice president of technology product at Workday. Ajao pitched Workday senior management on a bigger push into predictive analytics and says he was surprised at the positive response.

In March 2015, Ajao and others pitched to Workday's steering committee the idea to set up their own fund to handle incoming interest from startups. Too often, the response had been to consider acquisition or let the relationship go, though Workday has made some meaningful investments like one in financial planning software startup Tidemark in June. The committee of investing heavy hitters—Workday's billionaire CEO and Greylock Partners investor Aneel Bhusri, board member and billionaire Yahoo founder Jerry Yang and New Enterprise Associates managing general partner Scott Sandell—told Ajao to go for it, provided Workday Ventures follow several clear guidelines.

Workday Ventures is focused entirely on data and machine learning startups at the early stage. It doesn't have a fixed fund size and is focused on strategic opportunities, not just dollar signs. And most importantly, Ajao says, it's instructed not to "over-complicate it."

As far as what profile Workday Ventures hopes to build in Silicon Valley, the fund will seek to emulate the success of Salesforce Ventures and Google Ventures, which identify opportunities without getting too conflicted with their main bodies. All five partners have technical or product backgrounds and three of them PhDs.

How a typical investment might work would be that Workday Ventures identifies an opportunity and then asks to join a round. The fund won't lead the round or ask for a board seat, but can make customer introductions to the Workday ecosystem once it's taken on. That approach has Ajao confident that the fund will be able to work harmoniously with venture firms such as Google Ventures and Sequoia Capital, both of which are co-investors in some of the fund's first portfolio companies. Investments announced so far include Jobr, Metanautix, ThinAir and Unbabel.

Workday will still make acquisitions where a direct fit is obvious, says Beck, but out of a separate team within the company. At most, Workday Ventures might make that introduction. The focus, both investors stress, will be on watching and talking to the portfolio startups, not on grooming them for sale.

"For Workday, this is a great learning opportunity," says Ajao. "There's no better place to learn about these machine-learning techniques than at the startups."

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